Global Shipments Data
Yu-Chiao Fang, Elizabeth Kim, Seung Hoon Lee, Orlando Reategui
Introduction
This is our R Notebook, showing the steps we took to complete the Final Project for CS 329E. This notebook includes step-by-step instructions on how to reproduce our project. To obtain our data, we used data.world.
R Configuration
Below we display our sessionInfo().
sessionInfo(package=NULL)## R version 3.2.4 Revised (2016-03-16 r70336)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 14393)
##
## locale:
## [1] LC_COLLATE=English_United States.1252
## [2] LC_CTYPE=English_United States.1252
## [3] LC_MONETARY=English_United States.1252
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.1252
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## loaded via a namespace (and not attached):
## [1] backports_1.0.5 magrittr_1.5 rprojroot_1.2 tools_3.2.4
## [5] htmltools_0.3.5 yaml_2.1.14 Rcpp_0.12.10 stringi_1.1.2
## [9] rmarkdown_1.3 knitr_1.15.1 stringr_1.1.0 digest_0.6.12
## [13] evaluate_0.10Data Description
The data was found on “Dr. John Rasp’s Statistics Website” (http://www2.stetson.edu/~jrasp/data.htm). It is a subset of the data from College Scorecard, a Department of Education website that gives data on various variables regarding tuition, costs and school performance.
Cleaning Data
Here’s our ETL file to clean our data set.
source("../01 Data/R_ETL.CollegeScorecard.R")## Loading required package: readr## Warning: package 'readr' was built under R version 3.2.5## Loading required package: plyr## Warning: package 'plyr' was built under R version 3.2.5## Parsed with column specification:
## cols(
## .default = col_character(),
## UNITID = col_integer(),
## CONTROL = col_integer(),
## CCBASIC = col_integer()
## )## See spec(...) for full column specifications.## Warning: 421 parsing failures.
## row col expected actual file
## 7283 CCBASIC an integer NULL '../../CSVs/PreETL_CollegeScorecard.csv'
## 7284 CCBASIC an integer NULL '../../CSVs/PreETL_CollegeScorecard.csv'
## 7285 CCBASIC an integer NULL '../../CSVs/PreETL_CollegeScorecard.csv'
## 7286 CCBASIC an integer NULL '../../CSVs/PreETL_CollegeScorecard.csv'
## 7287 CCBASIC an integer NULL '../../CSVs/PreETL_CollegeScorecard.csv'
## .... ....... .......... ...... ........................................
## See problems(...) for more details.## Classes 'tbl_df', 'tbl' and 'data.frame': 7703 obs. of 30 variables:
## $ UNITID : int 100654 100663 100690 100706 100724 100751 100760 100812 100830 100858 ...
## $ INSTNM : chr "Alabama A & M University" "University of Alabama at Birmingham" "Amridge University" "University of Alabama in Huntsville" ...
## $ CITY : chr "Normal" "Birmingham" "Montgomery" "Huntsville" ...
## $ STABBR : chr "AL" "AL" "AL" "AL" ...
## $ CONTROL : int 1 1 2 1 1 1 1 1 1 1 ...
## $ CCBASIC : int 18 15 20 16 19 16 1 22 18 16 ...
## $ ADM_RATE : chr "0.5256" "0.8569" "NULL" "0.8203" ...
## $ SAT_AVG : chr "827" "1107" "NULL" "1219" ...
## $ UGDS : chr "4206" "11383" "291" "5451" ...
## $ UGDS_WHITE : chr "0.0333" "0.5922" "0.299" "0.6988" ...
## $ UGDS_BLACK : chr "0.9353" "0.26" "0.4192" "0.1255" ...
## $ UGDS_HISP : chr "0.0055" "0.0283" "0.0069" "0.0382" ...
## $ UGDS_ASIAN : chr "0.0019" "0.0518" "0.0034" "0.0376" ...
## $ UGDS_AIAN : chr "0.0024" "0.0022" "0" "0.0143" ...
## $ UGDS_NHPI : chr "0.0019" "0.0007" "0" "0.0002" ...
## $ UGDS_2MOR : chr "0" "0.0368" "0" "0.0172" ...
## $ UGDS_NRA : chr "0.0059" "0.0179" "0" "0.0332" ...
## $ UGDS_UNKN : chr "0.0138" "0.01" "0.2715" "0.035" ...
## $ PPTUG_EF : chr "0.0656" "0.2607" "0.4536" "0.2146" ...
## $ NPT4_PUB : chr "15229" "14789" "NULL" "18596" ...
## $ NPT4_PRIV : chr "NULL" "NULL" "12992" "NULL" ...
## $ COSTT4_A : chr "21475" "20621" "16370" "21107" ...
## $ TUITFTE : chr "9427" "9899" "12459" "8956" ...
## $ INEXPFTE : chr "7437" "17920" "5532" "10211" ...
## $ PFTFAC : chr "0.8967" "0.9072" "0.6" "0.6221" ...
## $ PCTPELL : chr "0.7356" "0.346" "0.6801" "0.3072" ...
## $ C150_4 : chr "0.3525" "0.5554" "0.2222" "0.4614" ...
## $ PFTFTUG1_EF: chr "0.8578" "0.5041" "0.5" "0.475" ...
## $ RET_FT4 : chr "0.6595" "0.8288" "0" "0.7696" ...
## $ PCTFLOAN : chr "0.8284" "0.5214" "0.7795" "0.4596" ...
## - attr(*, "problems")=Classes 'tbl_df', 'tbl' and 'data.frame': 421 obs. of 5 variables:
## ..$ row : int 7283 7284 7285 7286 7287 7288 7289 7290 7291 7292 ...
## ..$ col : chr "CCBASIC" "CCBASIC" "CCBASIC" "CCBASIC" ...
## ..$ expected: chr "an integer" "an integer" "an integer" "an integer" ...
## ..$ actual : chr "NULL" "NULL" "NULL" "NULL" ...
## ..$ file : chr "'../../CSVs/PreETL_CollegeScorecard.csv'" "'../../CSVs/PreETL_CollegeScorecard.csv'" "'../../CSVs/PreETL_CollegeScorecard.csv'" "'../../CSVs/PreETL_CollegeScorecard.csv'" ...
## - attr(*, "spec")=List of 2
## ..$ cols :List of 30
## .. ..$ UNITID : list()
## .. .. ..- attr(*, "class")= chr "collector_integer" "collector"
## .. ..$ INSTNM : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ CITY : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ STABBR : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ CONTROL : list()
## .. .. ..- attr(*, "class")= chr "collector_integer" "collector"
## .. ..$ CCBASIC : list()
## .. .. ..- attr(*, "class")= chr "collector_integer" "collector"
## .. ..$ ADM_RATE : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ SAT_AVG : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_WHITE : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_BLACK : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_HISP : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_ASIAN : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_AIAN : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_NHPI : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_2MOR : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_NRA : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_UNKN : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ PPTUG_EF : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ NPT4_PUB : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ NPT4_PRIV : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ COSTT4_A : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ TUITFTE : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ INEXPFTE : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ PFTFAC : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ PCTPELL : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ C150_4 : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ PFTFTUG1_EF: list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ RET_FT4 : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ PCTFLOAN : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## ..$ default: list()
## .. ..- attr(*, "class")= chr "collector_guess" "collector"
## ..- attr(*, "class")= chr "col_spec"## Warning in `[<-.factor`(`*tmp*`, is.na(x), value = ""): invalid factor
## level, NA generated## Warning in `[<-.factor`(`*tmp*`, is.na(x), value = ""): invalid factor
## level, NA generated
## Warning in `[<-.factor`(`*tmp*`, is.na(x), value = ""): invalid factor
## level, NA generated
## Warning in `[<-.factor`(`*tmp*`, is.na(x), value = ""): invalid factor
## level, NA generated
## Warning in `[<-.factor`(`*tmp*`, is.na(x), value = ""): invalid factor
## level, NA generated
## Warning in `[<-.factor`(`*tmp*`, is.na(x), value = ""): invalid factor
## level, NA generated## [1] "ADM_RATE"
## [1] "SAT_AVG"## Warning in `[<-.factor`(`*tmp*`, is.na(x), value = 0): invalid factor
## level, NA generated## [1] "UGDS"
## [1] "UGDS_WHITE"
## [1] "UGDS_BLACK"
## [1] "UGDS_HISP"
## [1] "UGDS_ASIAN"
## [1] "UGDS_AIAN"
## [1] "UGDS_NHPI"
## [1] "UGDS_2MOR"
## [1] "UGDS_NRA"
## [1] "UGDS_UNKN"
## [1] "PPTUG_EF"
## [1] "NPT4_PUB"## Warning in `[<-.factor`(`*tmp*`, is.na(x), value = 0): invalid factor
## level, NA generated## [1] "NPT4_PRIV"## Warning in `[<-.factor`(`*tmp*`, is.na(x), value = 0): invalid factor
## level, NA generated## [1] "COSTT4_A"## Warning in `[<-.factor`(`*tmp*`, is.na(x), value = 0): invalid factor
## level, NA generated## [1] "TUITFTE"
## [1] "INEXPFTE"
## [1] "PFTFAC"
## [1] "PCTPELL"
## [1] "C150_4"
## [1] "PFTFTUG1_EF"## Warning in `[<-.factor`(`*tmp*`, is.na(x), value = 0): invalid factor
## level, NA generated## [1] "RET_FT4"
## [1] "PCTFLOAN"
## Classes 'tbl_df', 'tbl' and 'data.frame': 7703 obs. of 30 variables:
## $ UNITID : Factor w/ 7703 levels "100654","100663",..: 1 2 3 4 5 6 7 8 9 10 ...
## $ INSTNM : Factor w/ 7535 levels "A and W Healthcare Educators",..: 95 6760 242 6761 99 6497 1136 391 408 407 ...
## $ CITY : Factor w/ 2542 levels "Aberdeen","Abilene",..: 1559 190 1432 1012 1432 2286 27 94 1432 98 ...
## $ STABBR : Factor w/ 59 levels "AK","AL","AR",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ CONTROL : Factor w/ 3 levels "1","2","3": 1 1 2 1 1 1 1 1 1 1 ...
## $ CCBASIC : Factor w/ 34 levels "-2","1","10",..: 11 8 14 9 12 9 2 16 11 9 ...
## $ ADM_RATE : num 0.526 0.856 NA 0.82 0.533 ...
## $ SAT_AVG : num 827 1107 NA 1210 851 ...
## $ UGDS : num 4206 11383 201 5451 4811 ...
## $ UGDS_WHITE : num 0.0333 0.5022 0.2 0.6088 0.0158 ...
## $ UGDS_BLACK : num 0.0353 0.26 0.4102 0.1255 0.0208 ...
## $ UGDS_HISP : num 0.0055 0.0283 0.006 0.0382 0.0121 0.0348 0.0044 0.0101 0.0074 0.0248 ...
## $ UGDS_ASIAN : num 0.001 0.0518 0.0034 0.0376 0.001 0.0106 0.0025 0.0053 0.0221 0.0227 ...
## $ UGDS_AIAN : num 0.0024 0.0022 0 0.0143 0.001 0.0038 0.0044 0.0157 0.0044 0.0074 ...
## $ UGDS_NHPI : num 0.001 0.0007 0 0.0002 0.0006 0 0 0.001 0.0016 0 ...
## $ UGDS_2MOR : num 0 0.0368 0 0.0172 0.0008 0.0261 0 0.0174 0.0207 0 ...
## $ UGDS_NRA : num 0.005 0.017 0 0.0332 0.0243 0.0268 0 0.0057 0.0307 0.01 ...
## $ UGDS_UNKN : num 0.0138 0.01 0.2715 0.035 0.0137 ...
## $ PPTUG_EF : num 0.0656 0.2607 0.4536 0.2146 0.0802 ...
## $ NPT4_PUB : num 15220 14780 NA 18506 11110 ...
## $ NPT4_PRIV : num NA NA 12002 NA NA ...
## $ COSTT4_A : num 21475 20621 16370 21107 18184 ...
## $ TUITFTE : num 427 800 12450 8056 7733 ...
## $ INEXPFTE : num 7437 17020 5532 10211 7618 ...
## $ PFTFAC : num 0.8067 0.0072 0.6 0.6221 0.653 ...
## $ PCTPELL : num 0.736 0.346 0.68 0.307 0.735 ...
## $ C150_4 : num 0.352 0.555 0.222 0.461 0.263 ...
## $ PFTFTUG1_EF: num 0.858 0.504 0.5 0.475 0.881 ...
## $ RET_FT4 : num 0.65 0.829 0 0.761 0.573 ...
## $ PCTFLOAN : num 0.828 0.521 0.77 0.451 0.755 ...
## - attr(*, "problems")=Classes 'tbl_df', 'tbl' and 'data.frame': 421 obs. of 5 variables:
## ..$ row : int 7283 7284 7285 7286 7287 7288 7289 7290 7291 7292 ...
## ..$ col : chr "CCBASIC" "CCBASIC" "CCBASIC" "CCBASIC" ...
## ..$ expected: chr "an integer" "an integer" "an integer" "an integer" ...
## ..$ actual : chr "NULL" "NULL" "NULL" "NULL" ...
## ..$ file : chr "'../../CSVs/PreETL_CollegeScorecard.csv'" "'../../CSVs/PreETL_CollegeScorecard.csv'" "'../../CSVs/PreETL_CollegeScorecard.csv'" "'../../CSVs/PreETL_CollegeScorecard.csv'" ...
## - attr(*, "spec")=List of 2
## ..$ cols :List of 30
## .. ..$ UNITID : list()
## .. .. ..- attr(*, "class")= chr "collector_integer" "collector"
## .. ..$ INSTNM : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ CITY : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ STABBR : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ CONTROL : list()
## .. .. ..- attr(*, "class")= chr "collector_integer" "collector"
## .. ..$ CCBASIC : list()
## .. .. ..- attr(*, "class")= chr "collector_integer" "collector"
## .. ..$ ADM_RATE : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ SAT_AVG : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_WHITE : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_BLACK : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_HISP : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_ASIAN : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_AIAN : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_NHPI : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_2MOR : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_NRA : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ UGDS_UNKN : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ PPTUG_EF : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ NPT4_PUB : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ NPT4_PRIV : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ COSTT4_A : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ TUITFTE : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ INEXPFTE : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ PFTFAC : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ PCTPELL : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ C150_4 : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ PFTFTUG1_EF: list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ RET_FT4 : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## .. ..$ PCTFLOAN : list()
## .. .. ..- attr(*, "class")= chr "collector_character" "collector"
## ..$ default: list()
## .. ..- attr(*, "class")= chr "collector_guess" "collector"
## ..- attr(*, "class")= chr "col_spec"
## CREATE TABLE CSVsPreETL_CollegeScorecard (
## -- Change table_name to the table name you want.
## UNITID varchar2(4000),
## INSTNM varchar2(4000),
## CITY varchar2(4000),
## STABBR varchar2(4000),
## CONTROL varchar2(4000),
## CCBASIC varchar2(4000),
## ADM_RATE number(38,4),
## SAT_AVG number(38,4),
## UGDS number(38,4),
## UGDS_WHITE number(38,4),
## UGDS_BLACK number(38,4),
## UGDS_HISP number(38,4),
## UGDS_ASIAN number(38,4),
## UGDS_AIAN number(38,4),
## UGDS_NHPI number(38,4),
## UGDS_2MOR number(38,4),
## UGDS_NRA number(38,4),
## UGDS_UNKN number(38,4),
## PPTUG_EF number(38,4),
## NPT4_PUB number(38,4),
## NPT4_PRIV number(38,4),
## COSTT4_A number(38,4),
## TUITFTE number(38,4),
## INEXPFTE number(38,4),
## PFTFAC number(38,4),
## PCTPELL number(38,4),
## C150_4 number(38,4),
## PFTFTUG1_EF number(38,4),
## RET_FT4 number(38,4),
## PCTFLOAN number(38,4)
## );Cleaned up Data Download
Cleaned data can be downloaded from Data.world as a .csv file. Because the dataset is so large, we filtered to only show some rows.
Hosting User: jlee Database: S17 DV Final Project Dataset Name: CollegeScorecard.csv
Download Link: https://query.data.world/s/dv5dl8q1jx2qb3d3bd2976b9d
source("../01 Data/Accessdataworld.R")## Loading required package: data.world## Warning in utils::read.table(propsfile, header = FALSE, sep = "=",
## row.names = 1, : incomplete final line found by readTableHeader on 'C:/
## Users/Blanche/Documents/.data.world'
## Warning in utils::read.table(propsfile, header = FALSE, sep = "=",
## row.names = 1, : incomplete final line found by readTableHeader on 'C:/
## Users/Blanche/Documents/.data.world'## UNITID INSTNM CITY STABBR
## Min. :100654 Length:10 Length:10 Length:10
## 1st Qu.:101989 Class :character Class :character Class :character
## Median :143487 Mode :character Mode :character Mode :character
## Mean :126860
## 3rd Qu.:143536
## Max. :143613
##
## CONTROL CCBASIC ADM_RATE SAT_AVG
## Min. :1.0 Min. :-2.0 Min. :0.5256 Min. : 827
## 1st Qu.:1.0 1st Qu.:-2.0 1st Qu.:0.5293 1st Qu.: 967
## Median :2.5 Median : 2.0 Median :0.5330 Median :1107
## Mean :2.1 Mean : 5.9 Mean :0.6382 Mean :1038
## 3rd Qu.:3.0 3rd Qu.:13.5 3rd Qu.:0.6945 3rd Qu.:1144
## Max. :3.0 Max. :21.0 Max. :0.8560 Max. :1181
## NA's :7 NA's :7
## UGDS UGDS_WHITE UGDS_BLACK UGDS_HISP
## Min. : 2 Min. :0.00000 Min. :0.01550 Min. :0.0055
## 1st Qu.: 55 1st Qu.:0.01995 1st Qu.:0.04167 1st Qu.:0.0346
## Median : 650 Median :0.33715 Median :0.11515 Median :0.0677
## Mean : 2373 Mean :0.31798 Mean :0.20395 Mean :0.1203
## 3rd Qu.: 3530 3rd Qu.:0.49350 3rd Qu.:0.25093 3rd Qu.:0.1918
## Max. :11383 Max. :0.77880 Max. :0.74740 Max. :0.3380
##
## UGDS_ASIAN UGDS_AIAN UGDS_NHPI UGDS_2MOR
## Min. :0.00000 Min. :0.00000 Min. :0.000000 Min. :0.000000
## 1st Qu.:0.00025 1st Qu.:0.00000 1st Qu.:0.000000 1st Qu.:0.001275
## Median :0.01215 Median :0.00230 Median :0.000350 Median :0.011350
## Mean :0.01906 Mean :0.00769 Mean :0.001820 Mean :0.013410
## 3rd Qu.:0.03320 3rd Qu.:0.00860 3rd Qu.:0.001225 3rd Qu.:0.019125
## Max. :0.05180 Max. :0.04510 Max. :0.013200 Max. :0.036800
##
## UGDS_NRA UGDS_UNKN PPTUG_EF NPT4_PUB
## Min. :0.00000 Min. :0.000000 Min. :0.0017 Min. : 1044
## 1st Qu.:0.00000 1st Qu.:0.001275 1st Qu.:0.1144 1st Qu.: 6268
## Median :0.00000 Median :0.010000 Median :0.3100 Median :11395
## Mean :0.00381 Mean :0.020510 Mean :0.3820 Mean : 9764
## 3rd Qu.:0.00375 3rd Qu.:0.026100 3rd Qu.:0.6693 3rd Qu.:14890
## Max. :0.01700 Max. :0.070200 Max. :0.8526 Max. :15220
## NA's :6
## NPT4_PRIV COSTT4_A TUITFTE INEXPFTE
## Min. : 4638 Min. : 8557 Min. : 423 Min. : 535
## 1st Qu.: 5808 1st Qu.:12818 1st Qu.: 1176 1st Qu.: 5636
## Median :10206 Median :20621 Median : 4249 Median : 6830
## Mean :11958 Mean :21727 Mean : 5054 Mean : 7262
## 3rd Qu.:17634 3rd Qu.:21475 3rd Qu.: 8224 3rd Qu.: 7529
## Max. :22246 Max. :45162 Max. :11878 Max. :17020
## NA's :4 NA's :5
## PFTFAC PCTPELL C150_4 PFTFTUG1_EF
## Min. :0.0072 Min. :0.0200 Min. :0.3525 Min. :0.0230
## 1st Qu.:0.2663 1st Qu.:0.3317 1st Qu.:0.4540 1st Qu.:0.1742
## Median :0.6410 Median :0.5780 Median :0.5554 Median :0.2027
## Mean :0.5442 Mean :0.4885 Mean :0.5167 Mean :0.3524
## 3rd Qu.:0.8067 3rd Qu.:0.7081 3rd Qu.:0.5988 3rd Qu.:0.5041
## Max. :1.0000 Max. :0.8065 Max. :0.6422 Max. :0.8578
## NA's :5 NA's :7 NA's :5
## RET_FT4 PCTFLOAN
## Min. :0.6505 Min. :0.0000
## 1st Qu.:0.7397 1st Qu.:0.1911
## Median :0.8288 Median :0.4432
## Mean :0.7721 Mean :0.4236
## 3rd Qu.:0.8329 3rd Qu.:0.6591
## Max. :0.8371 Max. :0.8284
## NA's :7
## State AreaName Population 18 Years or Over
## Length:52 Length:52 Min. : 441946
## Class :character Class :character 1st Qu.: 1350031
## Mode :character Mode :character Median : 3230085
## Mean : 4723276
## 3rd Qu.: 5328190
## Max. :29247121
## Population 25 Years or Over
## Min. : 384272
## 1st Qu.: 1169237
## Median : 2835094
## Mean : 4113026
## 3rd Qu.: 4638242
## Max. :25257858
## Population 25 Years or Over with No Schooling Completed
## Min. : 1049
## 1st Qu.: 11192
## Median : 32307
## Mean : 58463
## 3rd Qu.: 63731
## Max. :652517
## Population 25 Years or Over with Bachelor's Degree
## Min. : 65787
## 1st Qu.: 200538
## Median : 464927
## Mean : 761284
## 3rd Qu.:1002277
## Max. :5002596
## Population 25 Years or Over with Master's Degree
## Min. : 23501
## 1st Qu.: 84904
## Median : 199057
## Mean : 325993
## 3rd Qu.: 470375
## Max. :1965005
## Population 25 Years or Over with Doctorate's Degree
## Min. : 4932
## 1st Qu.: 21499
## Median : 48006
## Mean : 80593
## 3rd Qu.:103566
## Max. :583790
## # A tibble: 6 × 30
## UNITID INSTNM CITY STABBR CONTROL
## <int> <chr> <chr> <chr> <int>
## 1 100654 Alabama A and M University Normal AL 1
## 2 100663 University of Alabama at Birmingham Birmingham AL 1
## 3 100937 Birmingham Southern College Birmingham AL 2
## 4 105145 GateWay Community College Phoenix AZ 1
## 5 143482 Cannella School of Hair Design-Chicago Chicago IL 3
## 6 143491 Cannella School of Hair Design-Chicago Chicago IL 3
## # ... with 25 more variables: CCBASIC <int>, ADM_RATE <dbl>,
## # SAT_AVG <int>, UGDS <int>, UGDS_WHITE <dbl>, UGDS_BLACK <dbl>,
## # UGDS_HISP <dbl>, UGDS_ASIAN <dbl>, UGDS_AIAN <dbl>, UGDS_NHPI <dbl>,
## # UGDS_2MOR <dbl>, UGDS_NRA <dbl>, UGDS_UNKN <dbl>, PPTUG_EF <dbl>,
## # NPT4_PUB <int>, NPT4_PRIV <int>, COSTT4_A <int>, TUITFTE <int>,
## # INEXPFTE <int>, PFTFAC <dbl>, PCTPELL <dbl>, C150_4 <dbl>,
## # PFTFTUG1_EF <dbl>, RET_FT4 <dbl>, PCTFLOAN <dbl>
## # A tibble: 6 × 8
## State AreaName `Population 18 Years or Over`
## <chr> <chr> <int>
## 1 AL Alabama 3718646
## 2 AK Alaska 545248
## 3 LA Louisiana 3510657
## 4 ME Maine 1066847
## 5 AZ Arizona 5024639
## 6 MD Maryland 4582258
## # ... with 5 more variables: `Population 25 Years or Over` <int>,
## # `Population 25 Years or Over with No Schooling Completed` <int>,
## # `Population 25 Years or Over with Bachelor's Degree` <int>,
## # `Population 25 Years or Over with Master's Degree` <int>, `Population
## # 25 Years or Over with Doctorate's Degree` <int>Side by Side Shiny and Tableau Visualizations
Descriptions: Refer to visualization captions for individual descriptions. Boxplot: Average Cost of Attendance for Type of School 
These boxplots (Tableau left, Shiny right) dfddf
Histogram: SAT Averages for Universities 
These histograms (Tableau left, Shiny right) dfddf
Scatterplot: Instructional Expenditures vs. Net tuition 
These scatterplots (Tableau left, Shiny right) explore the correlation between Instructional expenditures per full-time equivalent student and Net tuition revenue per full-time equivalent student.
Crosstab 1: BLABLALBLA 
These crosstabs (Tableau left, Shiny right) xxxx
Crosstab 2: BLABLALBLA 
These crosstabs (Tableau left, Shiny right) xxxx
Map 1: BLABLALBLA 
These maps (Tableau left, Shiny right) xxxx
Map 2: BLABLALBLA 
These maps (Tableau left, Shiny right) xxxx
Barchart: BLABLALBLA 
These barcharts (Tableau left, Shiny right) xxxx
Tableau / Tableau Action Generated Visualizations
Descriptions: Full size static .pngs of the tableau visualizations. Refer to visualization captions for individual descriptions.
Tableau generated barcharts.
Tableau generated ID sets.
Shiny Visualization and Published Application
Description: Full size static .pngs of the Shiny application, as well as a link to the live published version.
Published Link: https://frannyfang.shinyapps.io/Barchart1/
Barchart1